Datasets. The dataset used for pre-training, LUPerson [1]}, contains 4.18M unlabeled human images in total, collected from 50,534 online videos. To evaluate the performance on ReID tasks, we conduct experiments on two popular benchmarks, Market-1501 (Market) [2]} and MSMT17 [3]}. They contain 32,668 images of 1,501 identities and 126,441 images of 4,101 identities, respectively. Images in these two datasets are resized to \(256 \times 128\)  during training and inference stages. Standard evaluation protocols are used with the metrics of mean Average Precision (mAP) and Rank-1 accuracy.
